# -*- coding: utf-8 -*-
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from datetime import timedelta
from jms.dm.prescription.dm_business_reach_details_dt import jms_dm__dm_business_reach_details_dt
from jms.dm.prescription.dm_net_pre_reach_rate_dt import jms_dm__dm_net_pre_reach_rate_dt
from jms.dm.prescription.dm_city_pre_reach_rate_dt import jms_dm__dm_city_pre_reach_rate_dt

jms_dm__dm_business_reach_summary_dt = SparkSqlOperator(
    task_id='jms_dm__dm_business_reach_summary_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(hours=1),
    email=['jokic.wang@jtexpress.com'],
    name='jms_dm__dm_business_reach_summary_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/prescription/dm_business_reach_summary_dt/execute.hql',
    driver_memory='4G',
    driver_cores=1,
    executor_cores=4,
    executor_memory='6G',
    num_executors=25,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={
        'spark.dynamicAllocation.enabled': 'false',  # 动态资源开启
        'spark.shuffle.service.enabled': 'false',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors': 25,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 120,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode': 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead': '1G',  # 堆外内存
        'spark.sql.shuffle.partitions': 200,
        'spark.executor.extraJavaOptions': '-XX:+UseG1GC -XX:ParallelGCThreads=4'
    },
    hiveconf={
        'hive.exec.dynamic.partition': 'true',  # 动态分区
        'hive.exec.dynamic.partition.mode': 'nonstrict',
        'hive.exec.max.dynamic.partitions': 20,  # 每天生成 20 个分区
        'hive.exec.max.dynamic.partitions.pernode': 20  # 每天生成 20 个分区
    },
)

jms_dm__dm_business_reach_summary_dt << [
    jms_dm__dm_business_reach_details_dt,
    jms_dm__dm_net_pre_reach_rate_dt,
    jms_dm__dm_city_pre_reach_rate_dt
]
